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Spatio-Temporal Assessment of Vegetation Cover of Jodhpur City and Surrounding Areas

  • September 2018
Authors:
s.L. Borana at MBM University
s.L. Borana
  • MBM University
s.K. Yadav at DL Jodhpur
s.K. Yadav
  • DL Jodhpur
S. K. Parihar
S. K. Parihar
S. K. Parihar
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ABSTRACT: Vegetation cover found in arid zone of Western Rajasthan is a precious resource for environment and livelihood of local habitats. The Vegetation in arid and semi-arid regions experiences a phenomenal change in its growth pattern and is highly dynamic. Various type of seasonal and scattered vegetation like Prosopis cineraria (Khejri), Salvadora oleoides (Meetha jal) Tecomella undulate (Rohida), Acacia senegal (Kumat), Capparis decidua (ker) and Azadirachta indica (neem) are the dominant tree species present in the arid area. Satellite imagery can be very useful in monitoring the vegetation. The main objective of the study is to find out changes among vegetation coverage over the period 2000 to 2010. These Changes are due to increasing population and subsequent anthropogenic activity in the past decades. Satellite data of LANDSAT and IRS L-3 were used for preparation of vegetation density and land use maps of the respective periods. Normalized Difference Vegetation Index (NDVI) supported by GIS was employed to detect vegetation changes. Results revealed significant changes in vegetation cover of the area during the study period. Such studies on temporal analysis of vegetation can help in monitoring the pattern and distribution across the city area for attaining sustainability of natural environment. KEYWORDS: Satellite Data, NDVI, Vegetation, GIS, Remote Sensing, Change Detection.
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ISSN(Online): 2320-9801
ISSN (Print): 2320-9798
International Journal of Innovative Research in Computer
and Communication Engineering
(A High Impact Factor, Monthly, Peer Reviewed Journal)
Website: www.ijircce.com
Vol. 5, Issue 10, October 2017
Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2017. 0510020 16224
Spatio-Temporal Assessment of Vegetation
Cover of Jodhpur City and Surrounding
Areas
S. L. Borana 1, S.K.Yadav 1 , S.K.Parihar2
Scientist, Remote Sensing Group, DL, Jodhpur, Rajasthan, India1
Professor, Dept. of Mining, MBM Engineering College, J.N.V.U, Jodhpur, Rajasthan, India2
ABSTRACT: Vegetation cover found in arid zone of Western Rajasthan is a precious resource for environment and
livelihood of local habitats. The Vegetation in arid and semi-arid regions experiences a phenomenal change in its
growth pattern and is highly dynamic. Various type of seasonal and scattered vegetation like Prosopis cineraria
(Khejri), Salvadora oleoides (Meetha jal) Tecomella undulate (Rohida), Acacia senegal (Kumat), Capparis decidua
(ker) and Azadirachta indica (neem) are the dominant tree species present in the arid area. Satellite imagery can be
very useful in monitoring the vegetation. The main objective of the study is to find out changes among vegetation
coverage over the period 2000 to 2010. These Changes are due to increasing population and subsequent anthropogenic
activity in the past decades. Satellite data of LANDSAT and IRS L-3 were used for preparation of vegetation density
and land use maps of the respective periods. Normalized Difference Vegetation Index (NDVI) supported by GIS was
employed to detect vegetation changes. Results revealed significant changes in vegetation cover of the area during the
study period. Such studies on temporal analysis of vegetation can help in monitoring the pattern and distribution across
the city area for attaining sustainability of natural environment.
KEYWORDS: Satellite Data, NDVI, Vegetation, GIS, Remote Sensing, Change Detection.
I. INTRODUCTION
A geographic Information System (GIS) can be as simple as points plotted on a paper map with some attribute
attached to the points.GIS today involves sophisticated software and can be integrated with Remote Sensing (RS)
technologies to provide monitoring of vegetation. The key element of GIS is that attributes are related spatial and some
system is utilized to process and analyze these relationships. Urban growth and its associated population increase is a
major factor which has altered natural vegetation cover. This has resulted in a significant effect on local weather and
climate. The use of remote sensing data in recent times has been of immense help in monitoring the changing pattern of
vegetation. Change detection, as defined is the temporal effects as variation in spectral response involves situations
where the spectral characteristics of the vegetation or other cover type in a given location change over time. The
vegetation is one of the invaluable natural resources which changes spatio- temporally in its extent and distribution.
Hence, reliable information on the extent and distribution of vegetation types is pre-requisite for natural resource
management and planning. As the vegetation types in tropical part of India represents diverse formations, on screen
visual image interpretation approach was found to be suitable to delineate various vegetation types. In the present
study, Landsat TM and IRS P6 LISS III data which is having spatial resolution 30m & 23.5 m respectively was used to
generate baseline information of vegetation types of Jodhpur city and surrounding area. The objective of the present
study was to develop detailed vegetation type map using visual image interpretation technique and information
collected from Ground Truth surveys.
ISSN(Online): 2320-9801
ISSN (Print): 2320-9798
International Journal of Innovative Research in Computer
and Communication Engineering
(A High Impact Factor, Monthly, Peer Reviewed Journal)
Website: www.ijircce.com
Vol. 5, Issue 10, October 2017
Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2017. 0510020 16225
II. STUDY AREA
Jodhpur city is located at a latitude of 26º 18' North and longitude of 73º 1' East and is located in the middle of the
Thar Desert tract of western Rajasthan (Fig.1a). Its general topography is characterized by the hills located in the North
and North-west. Jodhpur city is located at an average altitude of 241 m above Mean Sea Level at railway station with
fort and old city being much higher at 367.83 m and between 277.21m to 245.50 m respectively. The city has a natural
drainage slope from North-North East to South-South East towards Jojari River. The economy of Jodhpur thrives on
industrial goods and cultural heritage.
Fig.1(a). Location Map of the Study Area.
ISSN(Online): 2320-9801
ISSN (Print): 2320-9798
International Journal of Innovative Research in Computer
and Communication Engineering
(A High Impact Factor, Monthly, Peer Reviewed Journal)
Website: www.ijircce.com
Vol. 5, Issue 10, October 2017
Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2017. 0510020 16226
III. METHODS AND MATERIAL
False Colour Images of LANDSAT data on scale 1:50,000 for last one decade with Survey of India (SoI) maps were
used in the present study (Table No-1). The LANDSAT satellite Image is used to image processing for estimation of
NDVI. The software ERDAS-9.2 and ARCGIS-9.3 is used for data acquisition and processing. The detailed
methodology adopted for this work is given in Fig-1(b).
Table No-1 The Satellite Data used in the Study Area.
RS Data
Resolution
Path/Row
Acquisition
Landsat TM
30 m
149/42
Oct 2000
Landsat TM
30m
149/42
Oct 2010
IRS L
-
3
23.5m
92/53
Oct 2010
Table No-2. Band Combination
LANDSAT
Imageries
Band Combination
B
lue
Green
Red
True Colour Composite
1
2
3
False Colour Composite
2
3
4
NDVI Data
(Band 4
-
Band 3)/ (Band 4+ Band 3)
Fig.1(b) Methodology Flow Chart
ISSN(Online): 2320-9801
ISSN (Print): 2320-9798
International Journal of Innovative Research in Computer
and Communication Engineering
(A High Impact Factor, Monthly, Peer Reviewed Journal)
Website: www.ijircce.com
Vol. 5, Issue 10, October 2017
Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2017. 0510020 16227
IV. RESULTS AND DISCUSSION
The objective of present study was to generate a LU/LC features and change detection using remote sensing and
Geological Information System (GIS). The observation for the highly declining of vegetation cover, limited availability
and extinction of trees is also reported. The NDVI maps of Jodhpur city for both the years reveal four classes viz- water
bodies, mining area, vegetation/ forest and other land. NDVI values for each class of vegetation cover are detected. The
geospatial data generated on vegetation type maps are prime input for landscape ecological analysis.
(A) NDVI MAPPING OF THE STUDY AREA
The Normalized Difference Vegetation Index (NDVI) values for study area varied mostly from -0.56 to 0.63. As it
can be seen clearly the forest area has maximum NDVI values then comes the non forest area followed by the
habitation, mines and finally water body shows the least. From Fig.2 it is clear that most area in 2000 was covered by
forest. In the 2010 NDVI maps, there is decrease in the forest area and the increase in mining area can be clearly seen.
The area occupied by the mines and settlements has low NDVI values nearer to zero. Table-1 shows the variation of
NDVI values for different classes in the year 2010.
Fig.2. NDVI map based on the Landsat Satellite Data.
Table No-3: NDVI values and Class Types
S.No
.
Class Type
NDVI
1
Forest/Vegetation
0.29 to 0.63
2
Mining Area
-
0.27 to 0.00
3
Water body
-
0.56 to
-
0.44
4
Other Land
0.10 to 0.29
a) 2000 b) 2010
ISSN(Online): 2320-9801
ISSN (Print): 2320-9798
International Journal of Innovative Research in Computer
and Communication Engineering
(A High Impact Factor, Monthly, Peer Reviewed Journal)
Website: www.ijircce.com
Vol. 5, Issue 10, October 2017
Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2017. 0510020 16228
Table No-4. LU/LC Change statistics for the Decade (2000-2010)
(B) NDVI ASSESSMENT OF THE STUDY AREA
During 2000-10 decade the NDVI value is lies between -0.56 and +0.63 (Table No-3 and 4). The lower most NDVI
value in 2000 is –0.56. This value is close to -1 shows NDVI for no vegetation. The lower value of - 0.56 indicates the
presence aquatic plants in extremely low proportion. The NDVI value above zero to one indicates the terrestrial
vegetation with increase in their maximum proportion. The maximum NDVI value is 0.63 indicates comparative dense
vegetation cover. The overall highest value dense vegetation cover is +1. The maximum area of the Jodhpur city
belongs to the scrub and grasslands. The minimum area lies under water bodies. The NDVI is unable to separate
cropland from forest area. However, overall change of vegetation may be detected from substring NDVI map of year
2000 from year 2010 (Figure-3a&b). The final change detection map shows that water body is increases (0.083%) and
mining area also increases (4.73%) from 2000 to 2010 (Figure-4). The vegetation cover decrease (3.087%) and other
land is increases (18.872%) due to increase of population pressure on land.
Fig.3(a & b). Temporal NDVI Maps of the Study Area.
NDVI Classes
Area%
2000
Area %
2010
(%) change
2000-2010
Mining Area
18.18
22.91
4.73
Water Body
0.601
0.684
0.083
Vegetation/ Forest
24.369
21.282
-
3.087
Other Land
56.849
75.721
18.872
Total Area
100
100
--
a) 2000 b) 2010
ISSN(Online): 2320-9801
ISSN (Print): 2320-9798
International Journal of Innovative Research in Computer
and Communication Engineering
(A High Impact Factor, Monthly, Peer Reviewed Journal)
Website: www.ijircce.com
Vol. 5, Issue 10, October 2017
Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2017. 0510020 16229
Fig.4. Final NDVI Change Detection Map of the Study Area.
V. CONCLUSION
NDVI is an emerging technique from Remote Sensing and GIS technology to detect spatio-temporal change of
vegetation cover. The NDVI method gives superior results for vegetation varying in densities and also for scattered
vegetation from a multispectral remote sensing image. The vegetation analysis can be used in the events of natural
disasters to provide humanitarian aid and damage assessment.
ACKNOWLEDGEMENT
The authors are thankful to the Director DL, Jodhpur for help and encouragement during the study. The authors are
also thankful to Head Mining Department, J NV University, Jodhpur for his critical suggestion and encouragement.
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Hyperspectral Data Analysis for Desertic Vegetation of Jodhpur Area
Conference Paper
  • Feb 2020
Spectral signature provides unique characteristics of a tree species due to structure of leaf and chlorophyll content. Arid region has many varieties of vegetation species which are useful for livelihood and environment equilibrium. Objective of study was to acquire and examine the spectral charccteristics of the prominent vegetation viz. Azadirachtaindica, Senegalia senegal, Calotropis procera, Acacia nilotica and Capparis Decidua. In-situ spectral signature measurements were accomplished using Handheld Hyperspectral Spectroradiometer (SVC 1024 HR) in the 350-2500nm spectral range. Spectral signatures after processing were analyzed statistically and % reflectance value of every tree sample was map to get a visual conformity for variability of the different vegetation tree species. Various statistically techniques were also used for discrimination and analysis of spectral data. Statistical examination showed that Near-IR and Red waveband regions are optimum to discriminate tree species.
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Hyperspectral Data Analysis for Arid Vegetation Species : Smart & Sustainable Growth
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Comparative Evaluation of Spectral Indices and Sensors for Mapping of Urban Surface Water Bodies in Jodhpur Area : Smart & Sustainable Growth
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Remote sensing data increasingly used to identify and map open water bodies at comprehensive scales. The Jodhpur city experienced high urbanization in last one decade with population about 13Lakhs, and therefore needs effective public amenities alongwith safe water. In this research, compared accessible surface water bodies mapping approaches using seven spectral indices, viz. normalized difference water index (NDWI), tasseled cap wetness index (TCW), automated water extraction index (AWEIsh and AWEInsh), modified normalized difference water index (MNDWI), Water ratio index (WRI) and normalized difference vegetation index (NDVI) as well as two medium resolution sensors (Sentinel-2A and Landsat 8 OLI). The combinations of different water algorithms and satellite sensors were used to evaluate accuracy of the open water body. The results confirmed that water algorithms have high accuracies with Kappa Coefficients ranging from 0.12 to 0.98. The MNDWI water algorithms performed better than other water indices algorithms, and could be associated with pure water dominance in study area.The resultant water mapping from Sentinel-2A (10m) data has superior accuracies than Sentinel-2 (20m) and Landsat 8 OLI (30m). This research illustrates the enhanced performance in Sentinel-2A (10m) and Sentinel-2A (20m) for mapping of water body. The present study shows the availability of alternate water resources, which shall also be useful during frequent maintenance work of Rajeev Gandhi canal which supply water to whole city. The nearest neighbour technique is used to resample Sentibel-2A (10m) data of the visible and near IR bands to 20 m resolution bands to perform further analysis and comparisons.
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Change detection of vegetation cover Using Remote Sensing and GIS
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Full-text available
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Monitoring and management of urban sprawl require huge amount of information pertaining to natural and man-made features predominantly available in the area. Until lately, such a study could be achieved through days of exhaustive field data, thematic map and planning. Urban expansion is the key factors in changing land use/cover which has caused major problems like agricultural lands loss, water pollution, soil erosion and some social and economic disadvantages. One of the major advantages of Remote Sensing technique is timelines in the availability of information over large area and simultaneous observation making it possible to detect temporal changes. Geographical Information System (GIS) serves as a powerful tool for spatial and non-spatial analysis of remotely sensed data. This paper presents the spatial extent, magnitude and temporal behavior of land cover changes around Jodhpur city in past two decades. The second largest city of the state, Jodhpur is fast growing city surrounded by sand stone mining activities, rocky area, fallow land and industrial zones. While most of the commercial activities and unplanned settlement are located in the old city area and planned urban settlement, industries & mining area lies in the outskirts of the city. Satellite Data of Landsat, IRS-P6 L3, SOI toposheets and ground truth data were used for the change detection and preparation of GIS based outputs maps of the Jodhpur city and surrounding areas. These images were classified for finding different changes using urban sprawl techniques viz shannon's entropy and chi-square. Results revealed significant changes in land cover and urban settlements of the city during the study period. These results could help city planners and policy makers to attain and sustain future urban development.
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URBAN SETTLEMENT, PLANNING AND ENVIRONMENTAL STUDY OF JODHPUR CITY USING REMOTE SENSING AND GIS TECHNOLOGIES
Thesis
  • Nov 2015
The thesis includes the findings and results of Urban Sprawl growth, Land use, Geo- environmental status and public Amenities services, carried out in the Jodhpur City, Jodhpur district in Rajasthan. Jodhpur city is located at a latitude of 26º 18' North and longitude of 73º 1' East and in the middle of the Thar Desert tract of western Rajasthan about 250 km from the Pakistan border. The study area covers 594 sq. km. Jodhpur Municipal Corporation (JMC) area covers 228.51 sq. km and composed of 65 general electoral wards according to 2014. The city is located in saucer shaped basin at an average altitude of 241 m. above mean sea level. Jodhpur city is fast growing city surrounded by sand stone mining activities, military area and Industrial Zones. While most of the commercial activities and unplanned settlement are located in the old city area and planned urban settlement, industries & mining area lies in the outskirts of the city. The old city area is continuously developed area having densely populated residential and commercial land uses with no scope for physical expansion. This has pressurized development in the north eastern, south western and southern side. The main arterial roads leading to these areas are Nagaur Road, Jaipur Road, Barmer Road and Pali Road. Jodhpur is the third most industrialized district in Rajasthan. Jodhpur district accounts for 6% of the net domestic product from the Mining & Manufacturing Sector of the state. Urban sprawl is defined as the scattering of new development on isolated tracts, separated from other areas by vacant land. This result in increase in the built-up area and related changes in the urban landuse patterns, causing loss of productive agricultural lands, forest cover, other forms of greenery, loss in surface water bodies, depletion in ground water aquifers and increasing levels of air and water pollution; causing environmental problems. The process of urbanization is affected by population growth and migration. Infrastructure initiatives result in the growth of villages into towns, towns into cities and cities into metros involving large scale migration from rural to urban area. Sprawl is considered to be an unplanned outgrowth of urban centers along the periphery of cities, along highways and along the roads connecting to a city (Sudhira, et.al, 2003 and 2004). The main aim of this present study is to find out urban sprawl in Jodhpur city and suggest planning to provide utility services along with the sustainable environmental conditions in the study area . In order to serve this aim, following objectives have been put forth. to study existing landuse/landcover and urban growth with prediction, using satellite imagery in Jodhpur city. to identify various utility services and their distribution in wards of area. to monitor the mining and environmental impact analysis in the study area.
View
URBAN SETTLEMENT, PLANNING AND ENVIRONMENTAL STUDY OF JODHPUR CITY USING REMOTE SENSING AND GIS TECHNOLOGIES
Thesis
  • Nov 2015
The thesis includes the findings and results of Urban Sprawl growth, Land use, Geo- environmental status and public Amenities services, carried out in the Jodhpur City, Jodhpur district in Rajasthan. Jodhpur city is located at a latitude of 26º 18' North and longitude of 73º 1' East and in the middle of the Thar Desert tract of western Rajasthan about 250 km from the Pakistan border. The study area covers 594 sq. km. Jodhpur Municipal Corporation (JMC) area covers 228.51 sq. km and composed of 65 general electoral wards according to 2014. The city is located in saucer shaped basin at an average altitude of 241 m. above mean sea level. Jodhpur city is fast growing city surrounded by sand stone mining activities, military area and Industrial Zones. While most of the commercial activities and unplanned settlement are located in the old city area and planned urban settlement, industries & mining area lies in the outskirts of the city. The old city area is continuously developed area having densely populated residential and commercial land uses with no scope for physical expansion. This has pressurized development in the north eastern, south western and southern side. The main arterial roads leading to these areas are Nagaur Road, Jaipur Road, Barmer Road and Pali Road. Jodhpur is the third most industrialized district in Rajasthan. Jodhpur district accounts for 6% of the net domestic product from the Mining & Manufacturing Sector of the state. The main aim of this present study is to find out urban sprawl in Jodhpur city and suggest planning to provide utility services along with the sustainable environmental conditions in the study area . In order to serve this aim, following objectives have been put forth. to study existing landuse/landcover and urban growth with prediction, using satellite imagery in Jodhpur city. to identify various utility services and their distribution in wards of area. to monitor the mining and environmental impact analysis in the study area.
View
Review Article Digital Change Detection Techniques Using Remotely-Sensed Data
Article
  • Jun 1989
A variety of procedures for change detection based on comparison of multitemporal digital remote sensing data have been developed. An evaluation of results indicates that various procedures of change detection produce different maps of change even in the same environment.
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A Simple Physical Model of Vegetation Reflectance for Standardising Optical Satellite Imagery
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Monitoring vegetation using remote sensing is beset with difficulties. Primary among these are the variations of vegetation reflectance with sun zenith angle, view zenith angle, and terrain slope angle. To provide corrections of these effects, for visible and near-infrared light, we derive two simple physicial models of vegetation reflectance, both of which have three parameters. The first model, WAK I, is applicable when illumination is by direct light only; and the second model, WAK II, is applicable when illumination is by both diffuse and direct light. The models were tested by fitting them to reflectance data of Virginia pine, irrigated wheat, and alfalfa, at large sun zenith angles, and then comparing predictions of reflectance at small sun zenith angles with measurements. The process was then reversed to do the fitting on the small sun zenith measurements and the prediction of the large sun zenith measurements. Using this method of assessment, the WAK models were found to perform better than several other published models. The WAK models were used to derive a formula for the variation of reflectance with terrain slope angle, which was tested by measuring reflectances of microcanopies set up on different slopes in the laboratory. The formula permits topographic correction of vegetation reflectance without needing to know the bidirectional reflectance factor. The simplicity and robustness of the WAK models make them useful for general correction and calibration of remotely sensed imagery.
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Change detection of winter crops Coverage and Use of Landsat data with GIS
  • Jan 2004
  • 1-13
  • . Md.Rejaur Raheman
  • El
MD.Rejaur Raheman et..el (2004) "Change detection of winter crops Coverage and Use of Landsat data with GIS", The Journal of Geo-Environment Vol.4 PP1-13.
Spatio-Temporal land use/land cover changes analysis and monitoring in the Valencia municipality
  • Jan 2009
  • G Y Addis
Addis G. Y. (2009). Spatio-Temporal land use/land cover changes analysis and monitoring in the Valencia municipality, Spain. Dissertation Thesis.
Remote Sensing change detection in urban environments. Geospatial Technologies in urban environments: Policy practice and pixels
  • Jan 2007
  • 7-30
  • J R Jensen
  • J Im
Jensen, J.R. and Im, J. Remote Sensing change detection in urban environments. Geospatial Technologies in urban environments: Policy practice and pixels, 2nd ed., Springer-Verlag, Heidelberg, pp 7-30, 2007.